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Preoperative Hemoglobin Levels, Characteristics, and Resource Utilization in Total Knee Replacement Patients with An Anemia Diagnosis Versus without An Anemia Diagnosis: An Electronic Medical Record Analysis

2011· article· en· W4242599543 on OpenAlexaff
Jamie B. Forlenza, Lorie Ellis, Hélène Parisé, Marie‐Hélène Lafeuille, Patrick Lefèbvre

Bibliographic record

VenueBlood · 2011
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsMedicineAnemiaMedical recordHemoglobinSurgeryPopulationRetrospective cohort studyPediatricsInternal medicine

Abstract

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Abstract Abstract 2089 Purpose: This retrospective analysis describes preoperative hemoglobin (Hb) levels, characteristics, and resource use in total knee replacement (TKR) patients who had an anemia diagnosis as compared to those without an anemia diagnosis. Methods: Electronic medical records (EMR) from a large US integrated health delivery system were analyzed for the period 01/2004 to 09/2010. Adult patients with a TKR surgery record and ≥1 Hb measurement were studied. Patients with a hip or knee revision before or during surgery, with bilateral surgery, or with an emergency room (ER) visit on the surgery admission date were excluded. Patients were stratified into two groups based upon the presence or absence of an anemia diagnosis (ICD-9 codes 280.xx-285.xx) in the 90 days before or day of surgery. Hemoglobin levels measured in the 45 days prior to but excluding the day of surgery were analyzed. For patients with multiple Hb measurements, the earliest observed Hb measurement (defined as the measurement collected furthest in time from the date of surgery) was evaluated. Other clinical and demographic characteristics in the 90 days before or day of surgery and resource utilization in the 90 days pre-surgery were analyzed. Descriptive statistics were reported as frequencies and means±standard deviations, and groups were compared using the Pearson chi-square test for categorical variables and Student's t-test for continuous variables. Results: The total study population consisted of 2,984 TKR patients, of which, 9.1% (n=273) had an anemia diagnosis. In patients with an anemia diagnosis, the first anemia diagnosis in the EMR occurred 38±30 days before surgery. Patients with an anemia diagnosis versus those without an anemia diagnosis tended to be older (mean age 70.3±10.2 vs 67.5±10.0 years, respectively; p<0.001), have a lower proportion that were white (95.2% vs 98.5%, respectively; p<0.001), and have a higher comorbidity burden as measured by the Quan-Charlson Comorbidity Index (Q-CCI) (mean Q-CCI of 1.2±1.3 vs 0.6±1.0, respectively, p<0.001). The mean earliest Hb level for the total population was 13.7±1.3 g/dL and was <13 g/dL in 28.2% of TKR patients and <12 g/dL in 9.6% of TKR patients. The mean earliest Hb level was 12.5±1.3 g/dL in patients with an anemia diagnosis and was 13.8±1.2 g/dL for the group without an anemia diagnosis (p<0.001). Of patients with an anemia diagnosis, the majority (62.3%) had an earliest Hb level <13 g/dL (versus 24.8% of those without an anemia diagnosis; p<0.001) while 33.7% of those with an anemia diagnosis had an earliest Hb level <12 g/dL (versus 7.1% of those without an anemia diagnosis; p<0.001). Seven percent of patients with an anemia diagnosis had a hospitalization in the 90 days before TKR surgery versus 3.0% of those without an anemia diagnosis (p<0.001). In addition, 5.9% of the group with an anemia diagnosis had an ER visit versus 2.8% of those without an anemia diagnosis (p=0.005). In the 90 days pre-TKR surgery, the anemia diagnosis group had 5.0±2.7 days with an office/outpatient visit and 11.9±6.0 days with another-type service (e.g., prescription refill, administrative services) while the group without an anemia diagnosis had 3.6±2.0 (p<0.001) and 7.4±4.4 (p<0.001) days with these respective services. Conclusions: In this EMR database analysis, more than 9% of patients had an anemia diagnosis based upon ICD-9 codes in 90 days before or day of TKR surgery. Patients with an anemia diagnosis differed from those without an anemia diagnosis for certain characteristics including age, proportion who were white, comorbidity burden, and mean earliest Hb levels. The proportion of patients with a hospitalization in the 90 days preceding TKR surgery was significantly greater in patients with an anemia diagnosis as compared to those without an anemia diagnosis. In the total population, over 28% and 9% of patients had an earliest Hb value <13 g/dL and <12 g/dL, respectively, however, in patients without an anemia diagnosis, over 24% and 7% had an earliest Hb level <13 g/dL and <12 g/dL, respectively. This research provides further insight into preoperative Hb levels for a population of TKR patients with and without anemia diagnosis codes. Further research is warranted to better understand these variations between groups as well as the implications of these differences on preoperative management and post-operative outcomes in TKR populations. Disclosures: Forlenza: Janssen Scientific Affairs, LLC: Employment. Ellis:Janssen Scientific Affairs, LLC: Employment. Parise:Janssen Scientific Affairs, LLC: Consultancy. Lafeuille:Janssen Scientific Affairs, LLC: Consultancy. Lefebvre:Janssen Scientific Affairs, LLC: Consultancy.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.263
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2011
Admission routes1
Has abstractyes

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